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Physics 370

PHYS 370: Computational Methods in Physics

Prerequisites: PHYS 305, 306, and 308, or permission of instructor

Credit Hours: (3)

The goal of this class is to familiarize students with multiple methods of tackling problems in physics. Students will learn to use a variety of tools from spreadsheets (Excel or similar) to commercial math programs (Matlab or similar) to writing their own programs (Fortran/C and Visual Python or similar).

Detailed Description of Course

As noted above, students will learn to solve complex problems in physics using various numerical techniques. Some example problems that will be solved are realistic (including air resistance, spin, and lift) projectile motion, temperature diffusion throughout a material, complex gravitational forces involving 3 or more bodies, Monte Carlo methods of integration, frequency analysis of sound, and data fitting. To solve these problems, students will learn to utilize a variety of calculation techniques while also becoming familiar with the commonly used computational tools used in research and industry.

Detailed Description of Conduct of Course

The course itself will consist of regular short lectures. The remaining vast majority of the time will be spent by the students doing hands-on calculations and programming.

Student Goals and Objectives of the Course

The objectives for this course are that students will upon completion of the course be able to:

• use a spreadsheet to solve problems involving complex trajectories, temperature variations in a material with arbitrary heat sources, and advanced mechanics;
• use Matlab or other commercial math programs to solve problems involving complex gravitational systems, quantum mechanical systems, and optics; and
• write and compile code in C/Fortran/Visual Python or similar tools that can solve problems in physics using various common methods such as Runge-Kutta integration, Monte Carlo methods.

Assessment Measures

Students will turn in weekly assignments assessing their ability to solve problems numerically utilizing a variety of techniques. Students will also have a larger final project in which they will synthesize what they’ve learned to solve a more complex problem. The student will then present their work during the final exam period to the class.